package com.yourapp.pidinet;

import android.content.Context;
import android.graphics.Bitmap;
import android.graphics.Point;
import ai.onnxruntime.*;
import java.nio.FloatBuffer;
import java.util.*;

public class DocumentEdgeDetector {
    private static final String MODEL_NAME = "pidinet_mobile.onnx";
    private static final int INPUT_SIZE = 512;
    private static final float[] MEAN = {0.485f, 0.456f, 0.406f};
    private static final float[] STD = {0.229f, 0.224f, 0.225f};
    
    private OrtEnvironment env;
    private OrtSession session;
    private Context context;
    
    public DocumentEdgeDetector(Context context) throws OrtException {
        this.context = context;
        initializeModel();
    }
    
    private void initializeModel() throws OrtException {
        env = OrtEnvironment.getEnvironment();
        OrtSession.SessionOptions opts = new OrtSession.SessionOptions();
        opts.addCPU(false);
        
        // 从assets加载模型
        byte[] modelBytes = loadModelFromAssets();
        session = env.createSession(modelBytes, opts);
    }
    
    private byte[] loadModelFromAssets() {
        try {
            java.io.InputStream is = context.getAssets().open(MODEL_NAME);
            byte[] buffer = new byte[is.available()];
            is.read(buffer);
            is.close();
            return buffer;
        } catch (Exception e) {
            throw new RuntimeException("Failed to load model from assets", e);
        }
    }
    
    public DetectionResult detectDocument(Bitmap bitmap) {
        try {
            // 预处理
            float[][][] input = preprocessImage(bitmap);
            
            // 创建输入tensor
            long[] inputShape = {1, 3, INPUT_SIZE, INPUT_SIZE};
            OnnxTensor inputTensor = OnnxTensor.createTensor(env, input);
            
            // 推理
            Map<String, OnnxTensor> inputs = Collections.singletonMap("input", inputTensor);
            OrtSession.Result result = session.run(inputs);
            
            // 获取输出
            float[][][][] output = (float[][][][]) result.get(0).getValue();
            
            // 后处理
            return postprocessOutput(output[0][0], bitmap.getWidth(), bitmap.getHeight());
            
        } catch (Exception e) {
            e.printStackTrace();
            return new DetectionResult(false, null, null);
        }
    }
    
    private float[][][] preprocessImage(Bitmap bitmap) {
        // 调整大小到512x512
        Bitmap resized = Bitmap.createScaledBitmap(bitmap, INPUT_SIZE, INPUT_SIZE, true);
        
        float[][][] input = new float[3][INPUT_SIZE][INPUT_SIZE];
        
        for (int y = 0; y < INPUT_SIZE; y++) {
            for (int x = 0; x < INPUT_SIZE; x++) {
                int pixel = resized.getPixel(x, y);
                
                // 提取RGB并归一化
                float r = ((pixel >> 16) & 0xFF) / 255.0f;
                float g = ((pixel >> 8) & 0xFF) / 255.0f;
                float b = (pixel & 0xFF) / 255.0f;
                
                // 应用ImageNet标准化
                input[0][y][x] = (r - MEAN[0]) / STD[0];
                input[1][y][x] = (g - MEAN[1]) / STD[1];
                input[2][y][x] = (b - MEAN[2]) / STD[2];
            }
        }
        
        return input;
    }
    
    private DetectionResult postprocessOutput(float[][] edgeMap, int origWidth, int origHeight) {
        // 这里实现文档角点检测算法
        // 简化版本，实际使用中需要更复杂的轮廓检测
        
        List<Point> corners = new ArrayList<>();
        // TODO: 实现完整的轮廓检测和四边形拟合
        
        boolean hasDocument = corners.size() == 4;
        return new DetectionResult(hasDocument, corners, edgeMap);
    }
    
    public void close() {
        try {
            if (session != null) session.close();
            if (env != null) env.close();
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
    
    public static class DetectionResult {
        public final boolean hasDocument;
        public final List<Point> corners;
        public final float[][] edgeMap;
        
        DetectionResult(boolean hasDocument, List<Point> corners, float[][] edgeMap) {
            this.hasDocument = hasDocument;
            this.corners = corners;
            this.edgeMap = edgeMap;
        }
    }
}